Verification of Lost Data Packets and Regularizing Packets Transmission

Security in the network remains a major challenge which is highly susceptible to maliciousness. The routers especially are a major threat to the network. They can be malicious enough to disrupt the transmission of the data in the form of packets. In this paper, along with the detection of a malicious router, the transmission of packets is regularized to maximum extent possible. A Conditional Packet Buffering (CPB) algorithm is used to increase the through put of the router

AN EFFECTIVE SYSTEM TO IMPROVE THE CYBERBULLYING

The rapid growth of social networking is supplementing the progression of cyberbullying activities. Most of the individuals involved in these activities belong to the younger generations,   especially teenagers, who in the worst scenario are at more risk of suicidal attempts. This propose an effective approach to detect cyberbullying messages from social media through a SVM classifier algorithm. This present ranking algorithm to access highest visited link and also provide age verification before access the particular social media. The experiments show effectiveness of our approach

2-Methylxanthen-9-one

In the title compound, C14H10O2, the tricycle is not planar, being bent with a dihedral angle of 4.7 (1)° between the two benzene rings. In the crystal, π–π inter­actions between the six-membered rings of neighbouring mol­ecules [centroid–centroid distances = 3.580 (3) and 3.605 (3) Å] form stacks propagating along [101]

RADIOPROTECTIVE ACTIVITY OF FICUS RACEMOSA ETHANOL EXTRACT AGAINST ELECTRON BEAM INDUCED DNA DAMAGE IN VITRO, IN VIVO AND IN SILICO

Objective: To investigate the radioprotective effect of Ficus racemosa (Fr) ethanol stem bark extract against electron beam radiation (EBR) induced DNA damage using in vitro, in vivo and in silico models.Methods: The extract of Fr was tested against radiation induced DNA damage by exposing pBR322 plasmid to different EBR dose rates. Comet assay was conducted using mice which were exposed at 6Gy EBR. In silico study was performed by inhibiting p53 protein C-chain (1TUP C) using phyto chemicals of Fr.Results: The in vitro results revealed that, Fr at lower concentration (50µg) showed inhibitory effect on radiation induced DNA damage compared with control. Exposure of mice to 6Gy EBR increased comet parameters like TL (Tail length), OTM (Olive tail moment) and %T (percentage of DNA in the tail) of blood lymphocytes. Fr ethanol extract given orally prior to irradiation at a dose of 400 mg/kg body weight protected the DNA from the radiation damage. The phytochemicals of Fr showed clear interaction with p53 protein chain C, specifically binding to Arginine 248 (ARG248) and Arginine 273 (ARG273) amino acid residues thereby inhibiting the p53 protein-DNA interaction upon radiation.Conclusion: The present study indicates that Fr ethanol extract significantly reduced radiation induced DNA damage in vivo and in vitro. It also showed that the biologically active compounds of Fr have ability to inhibit wild p53 protein which is responsible for apoptosis; these compounds can be used as radioprotectors during chemotherapy to protect normal tissues surrounding cancerous tissue.Â

Optimization of neuropsychological scores at the baseline visit using evolutionary technique

The neuropsychological battery of scores, are the measures of cognitive domains of human brain, that are considered as important features to distinguish healthy subjects from the subjects, suffering from Mild Cognitive Impairment (MCI). The instances of about 5542, with four time visits are separated from the total collected instances of the National Alzheimer's Coordinating Center (NACC) database. The analysis of the selected data shows that the large number of subjects is identified for 66-75 and 76-85 age groups. The Genetic Algorithms (GA) applied on the neuropsychological scores at the baseline visit, selects the best subset of scores required for the clinical diagnosis, and these scores are evaluated by the logistic regression model using Area Under Curve (AUC), accuracy and Mean Squared Error (MSE) as the metric. Simulations result show that a highest classification accuracy of 0.9427, AUC of 0.9713

A Comprehensive Survey on Tools for Effective Alzheimer’s Disease Detection

Neuroimaging is considered as a valuable technique to study the structure and function of the human brain. Rapid advancement in medical imaging technologies has contributed significantly towards the development of neuroimaging tools. These tools focus on extracting and enhancing the relevant information from brain images, which facilitates neuroimaging experts to make better and quick decision for diagnosing enormous number of patients without requiring manual interventions. This paper describes the general outline of such tools including image file formats, ability to handle data from multiple modalities, supported platforms, implemented language, advantages and disadvantages. This brief review of tools gives a clear outlook for researchers to utilize existing techniques to handle the image data obtained from different modalities and focus further for improving and developing advanced tools

Evaluation of Neuropsychological Tests in Classification of Alzheimer’s Disease

Many neuropsychological tests are available to measure cognitive declinement in a person affected by Alzheimer’s disease. To evaluate his/her current stage in dementia and also to find the disease progression, it is necessary to perform a serial assessment of tests. As a result, the huge amount of data gets collected which depends on the number of neuropsychological tests performed to examine the patient and also with the number of visits to the clinic. From the previous correlation studies, it is observed that high computational time is required to process many neuropsychological tests. Therefore, the scores obtained from these tests are subjected to attribute selection algorithms. The six different attribute selection algorithms are used to rank the attributes, but the top four ranked attributes are consistent with InfoGain and OneR attribute evaluators. So, we subject the ordered attributes from these two

Phytoremediation: green to clean environmental heavy metal pollution

Many natural processes and anthropogenic activities lead to the persistent accumulation of non-biodegradable heavy metals in the environment. This contamination further has the potential to enter the food chain by a process called bioaccumulation and further, the concentration of heavy metal raises exponentially from lower to higher trophic levels as it is consumed called biomagnification. With the perspective of the consequences associated with heavy metal toxicity including risks to ecosystem and human health (mutagenic, carcinogenic, and teratogenic), the reclamation of toxic accumulates in soil and water is of paramount importance. Presently, clean-up technologies for heavy metals primarily concentrate on mitigating toxicity using physicochemical and mechanical methods such as soil incineration, excavation, landfilling, soil washing, solidification, and the application of electric fields. However, these are expensive, time-consuming, and also result in destructive changes to soil's physicochemical and biological properties, causing secondary pollution to the soil ecosystem. Therefore, the use of the inherent plant’s ability to absorb ionic compounds even at low concentrations near the soil-root interface can be effectively employed as a strategy to extract and remove or lower the bioavailable toxic metals and this phenomenon is called phytoremediation